Dataset statistics
| Number of variables | 9 |
|---|---|
| Number of observations | 4177 |
| Missing cells | 0 |
| Missing cells (%) | 0.0% |
| Duplicate rows | 0 |
| Duplicate rows (%) | 0.0% |
| Total size in memory | 497.8 KiB |
| Average record size in memory | 122.0 B |
Variable types
| Categorical | 1 |
|---|---|
| Numeric | 8 |
Length is highly correlated with Diameter and 6 other fields | High correlation |
Diameter is highly correlated with Length and 6 other fields | High correlation |
Height is highly correlated with Length and 6 other fields | High correlation |
Whole weight is highly correlated with Length and 6 other fields | High correlation |
Shucked weight is highly correlated with Length and 6 other fields | High correlation |
Viscera weight is highly correlated with Length and 6 other fields | High correlation |
Shell weight is highly correlated with Length and 6 other fields | High correlation |
Rings is highly correlated with Length and 6 other fields | High correlation |
Length is highly correlated with Diameter and 6 other fields | High correlation |
Diameter is highly correlated with Length and 6 other fields | High correlation |
Height is highly correlated with Length and 6 other fields | High correlation |
Whole weight is highly correlated with Length and 6 other fields | High correlation |
Shucked weight is highly correlated with Length and 5 other fields | High correlation |
Viscera weight is highly correlated with Length and 6 other fields | High correlation |
Shell weight is highly correlated with Length and 6 other fields | High correlation |
Rings is highly correlated with Length and 5 other fields | High correlation |
Length is highly correlated with Diameter and 5 other fields | High correlation |
Diameter is highly correlated with Length and 5 other fields | High correlation |
Height is highly correlated with Length and 6 other fields | High correlation |
Whole weight is highly correlated with Length and 5 other fields | High correlation |
Shucked weight is highly correlated with Length and 5 other fields | High correlation |
Viscera weight is highly correlated with Length and 5 other fields | High correlation |
Shell weight is highly correlated with Length and 6 other fields | High correlation |
Rings is highly correlated with Height and 1 other fields | High correlation |
Sex is highly correlated with Length and 6 other fields | High correlation |
Length is highly correlated with Sex and 7 other fields | High correlation |
Diameter is highly correlated with Sex and 7 other fields | High correlation |
Height is highly correlated with Length and 6 other fields | High correlation |
Whole weight is highly correlated with Sex and 7 other fields | High correlation |
Shucked weight is highly correlated with Sex and 7 other fields | High correlation |
Viscera weight is highly correlated with Sex and 7 other fields | High correlation |
Shell weight is highly correlated with Sex and 7 other fields | High correlation |
Rings is highly correlated with Sex and 7 other fields | High correlation |
Reproduction
| Analysis started | 2022-02-15 20:03:38.678187 |
|---|---|
| Analysis finished | 2022-02-15 20:03:46.276083 |
| Duration | 7.6 seconds |
| Software version | pandas-profiling v3.1.0 |
| Download configuration | config.json |
| Distinct | 3 |
|---|---|
| Distinct (%) | 0.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 236.7 KiB |
| M | |
|---|---|
| I | |
| F |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | M |
|---|---|
| 2nd row | M |
| 3rd row | F |
| 4th row | M |
| 5th row | I |
Common Values
| Value | Count | Frequency (%) |
| M | 1528 | |
| I | 1342 | |
| F | 1307 |
Length
| Distinct | 2 |
|---|---|
| Distinct (%) | < 0.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Memory size | 236.6 KiB |
| 0 | |
|---|---|
| 1 |
Length
| Max length | 1 |
|---|---|
| Median length | 1 |
| Mean length | 1 |
| Min length | 1 |
Characters and Unicode
| Total characters | 0 |
|---|---|
| Distinct characters | 0 |
| Distinct categories | 0 ? |
| Distinct scripts | 0 ? |
| Distinct blocks | 0 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Unique | 0 ? |
|---|---|
| Unique (%) | 0.0% |
Sample
| 1st row | 0 |
|---|---|
| 2nd row | 0 |
| 3rd row | 1 |
| 4th row | 0 |
| 5th row | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 2868 | |
| 1 | 1307 |
Length
Quantile statistics
| Minimum | 0.001 |
|---|---|
| 5-th percentile | 0.0524 |
| Q1 | 0.186 |
| median | 0.336 |
| Q3 | 0.502 |
| 95-th percentile | 0.7402 |
| Maximum | 1.488 |
| Range | 1.487 |
| Interquartile range (IQR) | 0.316 |
Descriptive statistics
| Standard deviation | 0.221962949 |
|---|---|
| Coefficient of variation (CV) | 0.6176489417 |
| Kurtosis | 0.5951236784 |
| Mean | 0.3593674886 |
| Median Absolute Deviation (MAD) | 0.1585 |
| Skewness | 0.7190979218 |
| Sum | 1501.078 |
| Variance | 0.04926755074 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0.175 | 11 | 0.3% |
| 0.2505 | 10 | 0.2% |
| 0.165 | 9 | 0.2% |
| 0.097 | 9 | 0.2% |
| 0.21 | 9 | 0.2% |
| 0.419 | 9 | 0.2% |
| 0.302 | 9 | 0.2% |
| 0.096 | 9 | 0.2% |
| 0.2025 | 9 | 0.2% |
| 0.2945 | 9 | 0.2% |
| Other values (1505) | 4084 |
| Value | Count | Frequency (%) |
| 0.001 | 1 | < 0.1% |
| 0.0025 | 1 | < 0.1% |
| 0.0045 | 2 | |
| 0.005 | 3 | |
| 0.0055 | 2 | |
| 0.0065 | 3 | |
| 0.007 | 1 | < 0.1% |
| 0.0075 | 4 | |
| 0.008 | 1 | < 0.1% |
| 0.0085 | 1 | < 0.1% |
| Value | Count | Frequency (%) |
| 1.488 | 1 | |
| 1.351 | 1 | |
| 1.3485 | 1 | |
| 1.253 | 1 | |
| 1.2455 | 1 | |
| 1.2395 | 2 | |
| 1.232 | 1 | |
| 1.1965 | 1 | |
| 1.1945 | 1 | |
| 1.1705 | 1 |
Viscera weight
Real number (ℝ≥0)
HIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATIONHIGH CORRELATION| Distinct | 880 |
|---|---|
| Distinct (%) | 21.1% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.1805936079 |
| Minimum | 0.0005 |
|---|---|
| Maximum | 0.76 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 32.8 KiB |
Quantile statistics
| Minimum | 0.0005 |
|---|---|
| 5-th percentile | 0.027 |
| Q1 | 0.0935 |
| median | 0.171 |
| Q3 | 0.253 |
| 95-th percentile | 0.3796 |
| Maximum | 0.76 |
| Range | 0.7595 |
| Interquartile range (IQR) | 0.1595 |
Descriptive statistics
| Standard deviation | 0.1096142503 |
|---|---|
| Coefficient of variation (CV) | 0.6069663902 |
| Kurtosis | 0.084011749 |
| Mean | 0.1805936079 |
| Median Absolute Deviation (MAD) | 0.0795 |
| Skewness | 0.5918521514 |
| Sum | 754.3395 |
| Variance | 0.01201528386 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0.1715 | 15 | 0.4% |
| 0.196 | 14 | 0.3% |
| 0.037 | 13 | 0.3% |
| 0.061 | 13 | 0.3% |
| 0.0575 | 13 | 0.3% |
| 0.2195 | 13 | 0.3% |
| 0.156 | 12 | 0.3% |
| 0.096 | 12 | 0.3% |
| 0.0265 | 12 | 0.3% |
| 0.1625 | 12 | 0.3% |
| Other values (870) | 4048 |
| Value | Count | Frequency (%) |
| 0.0005 | 2 | < 0.1% |
| 0.002 | 1 | < 0.1% |
| 0.0025 | 2 | < 0.1% |
| 0.003 | 3 | |
| 0.0035 | 3 | |
| 0.004 | 1 | < 0.1% |
| 0.0045 | 4 | |
| 0.005 | 7 | |
| 0.0055 | 6 | |
| 0.006 | 2 | < 0.1% |
| Value | Count | Frequency (%) |
| 0.76 | 1 | |
| 0.6415 | 1 | |
| 0.59 | 1 | |
| 0.575 | 1 | |
| 0.5745 | 1 | |
| 0.564 | 1 | |
| 0.55 | 1 | |
| 0.541 | 2 | |
| 0.5265 | 1 | |
| 0.526 | 1 |
| Distinct | 926 |
|---|---|
| Distinct (%) | 22.2% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 0.2388308595 |
| Minimum | 0.0015 |
|---|---|
| Maximum | 1.005 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 32.8 KiB |
Quantile statistics
| Minimum | 0.0015 |
|---|---|
| 5-th percentile | 0.0384 |
| Q1 | 0.13 |
| median | 0.234 |
| Q3 | 0.329 |
| 95-th percentile | 0.48 |
| Maximum | 1.005 |
| Range | 1.0035 |
| Interquartile range (IQR) | 0.199 |
Descriptive statistics
| Standard deviation | 0.1392026695 |
|---|---|
| Coefficient of variation (CV) | 0.5828504316 |
| Kurtosis | 0.5319261262 |
| Mean | 0.2388308595 |
| Median Absolute Deviation (MAD) | 0.0995 |
| Skewness | 0.6209268251 |
| Sum | 997.5965 |
| Variance | 0.0193773832 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 0.275 | 43 | 1.0% |
| 0.25 | 42 | 1.0% |
| 0.315 | 40 | 1.0% |
| 0.265 | 40 | 1.0% |
| 0.185 | 40 | 1.0% |
| 0.17 | 37 | 0.9% |
| 0.285 | 37 | 0.9% |
| 0.175 | 36 | 0.9% |
| 0.3 | 36 | 0.9% |
| 0.22 | 36 | 0.9% |
| Other values (916) | 3790 |
| Value | Count | Frequency (%) |
| 0.0015 | 1 | < 0.1% |
| 0.003 | 1 | < 0.1% |
| 0.0035 | 1 | < 0.1% |
| 0.004 | 2 | < 0.1% |
| 0.005 | 12 | |
| 0.006 | 1 | < 0.1% |
| 0.0065 | 1 | < 0.1% |
| 0.007 | 1 | < 0.1% |
| 0.0075 | 1 | < 0.1% |
| 0.008 | 4 | 0.1% |
| Value | Count | Frequency (%) |
| 1.005 | 1 | < 0.1% |
| 0.897 | 1 | < 0.1% |
| 0.885 | 2 | |
| 0.85 | 1 | < 0.1% |
| 0.815 | 1 | < 0.1% |
| 0.7975 | 1 | < 0.1% |
| 0.78 | 1 | < 0.1% |
| 0.76 | 1 | < 0.1% |
| 0.726 | 1 | < 0.1% |
| 0.725 | 3 |
| Distinct | 28 |
|---|---|
| Distinct (%) | 0.7% |
| Missing | 0 |
| Missing (%) | 0.0% |
| Infinite | 0 |
| Infinite (%) | 0.0% |
| Mean | 9.933684463 |
| Minimum | 1 |
|---|---|
| Maximum | 29 |
| Zeros | 0 |
| Zeros (%) | 0.0% |
| Negative | 0 |
| Negative (%) | 0.0% |
| Memory size | 32.8 KiB |
Quantile statistics
| Minimum | 1 |
|---|---|
| 5-th percentile | 6 |
| Q1 | 8 |
| median | 9 |
| Q3 | 11 |
| 95-th percentile | 16 |
| Maximum | 29 |
| Range | 28 |
| Interquartile range (IQR) | 3 |
Descriptive statistics
| Standard deviation | 3.224169032 |
|---|---|
| Coefficient of variation (CV) | 0.324569302 |
| Kurtosis | 2.330687427 |
| Mean | 9.933684463 |
| Median Absolute Deviation (MAD) | 2 |
| Skewness | 1.114101898 |
| Sum | 41493 |
| Variance | 10.39526595 |
| Monotonicity | Not monotonic |
Histogram with fixed size bins (bins=28)
| Value | Count | Frequency (%) |
| 9 | 689 | |
| 10 | 634 | |
| 8 | 568 | |
| 11 | 487 | |
| 7 | 391 | |
| 12 | 267 | 6.4% |
| 6 | 259 | 6.2% |
| 13 | 203 | 4.9% |
| 14 | 126 | 3.0% |
| 5 | 115 | 2.8% |
| Other values (18) | 438 |
| Value | Count | Frequency (%) |
| 1 | 1 | < 0.1% |
| 2 | 1 | < 0.1% |
| 3 | 15 | 0.4% |
| 4 | 57 | 1.4% |
| 5 | 115 | 2.8% |
| 6 | 259 | 6.2% |
| 7 | 391 | |
| 8 | 568 | |
| 9 | 689 | |
| 10 | 634 |
| Value | Count | Frequency (%) |
| 29 | 1 | < 0.1% |
| 27 | 2 | < 0.1% |
| 26 | 1 | < 0.1% |
| 25 | 1 | < 0.1% |
| 24 | 2 | < 0.1% |
| 23 | 9 | 0.2% |
| 22 | 6 | 0.1% |
| 21 | 14 | |
| 20 | 26 | |
| 19 | 32 |
Histogram of lengths of the category
Pie chart
Histogram of lengths of the category
Pie chart
Histogram of lengths of the category
Pie chart
| Value | Count | Frequency (%) |
| 0 | 2647 | |
| 1 | 1528 |
Most occurring characters
| Value | Count | Frequency (%) |
| No values found. | ||
Most occurring categories
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per category
Most occurring scripts
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per script
Most occurring blocks
| Value | Count | Frequency (%) |
| No values found. | ||
Most frequent character per block
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Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
Spearman's ρ
The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
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Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
Pearson's r
The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
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Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Kendall's τ
Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
Cramér's V (φc)
Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.>>>>>> 4e89958cb6cafc8e751ef012b005e36d3fc5002c
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Phik (φk)
Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.Phik (φk)
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A simple visualization of nullity by column.
A simple visualization of nullity by column.
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Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
First rows
| Sex | Length | Diameter | Height | Whole weight | Shucked weight | Viscera weight | Shell weight | Rings | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | M | 0.455 | 0.365 | 0.095 | 0.5140 | 0.2245 | 0.1010 | 0.150 | 15 |
| 1 | M | 0.350 | 0.265 | 0.090 | 0.2255 | 0.0995 | 0.0485 | 0.070 | 7 |
| 2 | F | 0.530 | 0.420 | 0.135 | 0.6770 | 0.2565 | 0.1415 | 0.210 | 9 |
| 3 | M | 0.440 | 0.365 | 0.125 | 0.5160 | 0.2155 | 0.1140 | 0.155 | 10 |
| 4 | I | 0.330 | 0.255 | 0.080 | 0.2050 | 0.0895 | 0.0395 | 0.055 | 7 |
| 5 | I | 0.425 | 0.300 | 0.095 | 0.3515 | 0.1410 | 0.0775 | 0.120 | 8 |
| 6 | F | 0.530 | 0.415 | 0.150 | 0.7775 | 0.2370 | 0.1415 | 0.330 | 20 |
| 7 | F | 0.545 | 0.425 | 0.125 | 0.7680 | 0.2940 | 0.1495 | 0.260 | 16 |
| 8 | M | 0.475 | 0.370 | 0.125 | 0.5095 | 0.2165 | 0.1125 | 0.165 | 9 |
| 9 | F | 0.550 | 0.440 | 0.150 | 0.8945 | 0.3145 | 0.1510 | 0.320 | 19 |
Last rows
| Sex | Length | Diameter | Height | Whole weight | Shucked weight | Viscera weight | Shell weight | Rings | |
|---|---|---|---|---|---|---|---|---|---|
| 4167 | M | 0.500 | 0.380 | 0.125 | 0.5770 | 0.2690 | 0.1265 | 0.1535 | 9 |
| 4168 | F | 0.515 | 0.400 | 0.125 | 0.6150 | 0.2865 | 0.1230 | 0.1765 | 8 |
| 4169 | M | 0.520 | 0.385 | 0.165 | 0.7910 | 0.3750 | 0.1800 | 0.1815 | 10 |
| 4170 | M | 0.550 | 0.430 | 0.130 | 0.8395 | 0.3155 | 0.1955 | 0.2405 | 10 |
| 4171 | M | 0.560 | 0.430 | 0.155 | 0.8675 | 0.4000 | 0.1720 | 0.2290 | 8 |
| 4172 | F | 0.565 | 0.450 | 0.165 | 0.8870 | 0.3700 | 0.2390 | 0.2490 | 11 |
| 4173 | M | 0.590 | 0.440 | 0.135 | 0.9660 | 0.4390 | 0.2145 | 0.2605 | 10 |
| 4174 | M | 0.600 | 0.475 | 0.205 | 1.1760 | 0.5255 | 0.2875 | 0.3080 | 9 |
| 4175 | F | 0.625 | 0.485 | 0.150 | 1.0945 | 0.5310 | 0.2610 | 0.2960 | 10 |
| 4176 | M | 0.710 | 0.555 | 0.195 | 1.9485 | 0.9455 | 0.3765 | 0.4950 | 12 |